
export CUDA=0



# export CHECKPOINT_DIR="jingheya/lotus-depth-g-v2-0-disparity"
# export CHECKPOINT_DIR="jingheya/lotus-depth-g-v2-1-disparity"
# export CHECKPOINT_DIR="jingheya/lotus-depth-d-v2-0-disparity"

# export CHECKPOINT_DIR="output/train-lotus-g-depth-bsz256-disparity"
# export CHECKPOINT_DIR="output/train-lotus-g-depth-bsz256"
# export CHECKPOINT_DIR="output/train-lotus-d-depth-bsz256"
# export CHECKPOINT_DIR="output/train-lotus-d-depth-bsz256-mixdata4"
# export CHECKPOINT_DIR="output/train-lotus-d-depth-bsz256-xyz-debug2"
# export CHECKPOINT_DIR="output/train-lotus-d-depth-bsz192-cleargrasp"
# export CHECKPOINT_DIR="output/train-lotus-d-depth-bsz256-xyz-booster-fixed"
# exp_name=train-lotus-d-depth-bsz256-xyz-booster-fixed-moge;


exp_name=my_test;


export CHECKPOINT_DIR="output/${exp_name}"






# jsonl_path=/share/project/cwm/shaocong.xu/exp/Lotus/data/cleargrasp-dataset-test-val_processed_synthetic_test/test.jsonl
# jsonl_path=/share/project/cwm/shaocong.xu/exp/Lotus/data/cleargrasp-dataset-test-val_processed_synthetic_val/test.jsonl
jsonl_path=/share/project/cwm/shaocong.xu/exp/Lotus/data/tricky_nogt_2025/test.jsonl


#!================================================================================
IFS='/' read -r -a parts <<< "$CHECKPOINT_DIR"
part1="${parts[0]}"
part2="${parts[1]}"



IFS='/' read -r -a parts <<< "$jsonl_path"
data_name="${parts[-2]}"





#!================================================================================
# export OUTPUT_DIR="output/${part2}#${data_name}#$RANDOM"
export OUTPUT_DIR="output/${exp_name}/eval#$RANDOM/"


export TASK_NAME="depth"

# export CHECKPOINT_DIR="jingheya/lotus-normal-g-v1-0"
# export OUTPUT_DIR="output/Normal_G_Infer"
# export TASK_NAME="normal"

export MODE="regression"
# export MODE="generation"

export TEST_IMAGES="assets/in-the-wild_example"


CUDA_VISIBLE_DEVICES=$CUDA python infer_test.py \
        --pretrained_model_name_or_path=$CHECKPOINT_DIR \
        --prediction_type="sample" \
        --seed=42 \
        --half_precision \
        --input_dir=$TEST_IMAGES \
        --task_name=$TASK_NAME \
        --mode=$MODE \
        --output_dir=$OUTPUT_DIR \
        --jsonl_path=${jsonl_path}
        




        #  \
        # --disparity 
        # --processing_res=0 # Defualt: 768. To obtain more fine-grained results, you can set `--processing_res=0` (original resolution) or a higher resolution. 



        